Images, such as charts, drawings, and pictures, may be represented as a two-dimensional matrix of picture elements (pixels). The spatial resolution and intensity level for each pixel are chosen to correspond to the particular output device used. For example, typical computer monitors display images at 75 dots per inch (DPI) and have 256 levels of intensity for each color. Such monitors use the additive primary colors, red, green, and blue (RGB), which can be combined to produce millions of colors and also black.
Typical hardcopy output devices, such as inkjet printers, are binary devices, meaning that for each pixel or possible dot location on the printed medium they can only print at two levels: on or off. Therefore, some means must be provided to convert the monitor-based version of the image (256 intensity levels per color), or another version of the color image, to the binary version (2 levels per color). These conversion methods are commonly referred to as halftoning. Halftoning methods are described in the book Digital Halftoning, by Robert Ulichney, The MIT Press, 1987, incorporated herein by reference.
One major approach to halftoning is error diffusion. The decision about whether or not to print a dot is based not only on the "ideal" intensity (i.e., one of the 256 possible intensities) for that pixel, but on what has happened before for previously processed pixels. The present invention is directed to an error diffusion technique.
It is assumed in the following explanation that the pixel intensity may range between 0 and 255. In error diffusion, at each point where a dot may be printed, the original image pixel intensity between 0-255, plus accumulated error, is compared to a previously chosen threshold value. If the image pixel intensity is greater than the threshold value, a dot (255 intensity) is assigned to that pixel. If not, no dot (0 intensity) is assigned. In either case, the intensity difference between the actual dot value assigned (0 or 255) and the ideal image pixel intensity plus accumulated error for that point is derived, and this difference becomes an error term that is "diffused" to other subsequently processed pixels. In other words, the diffused error term is added to the image pixel intensity plus the accumulated error of the subsequently processed pixels, and this total resultant image pixel intensity is then compared against the error diffusion threshold to determine whether a dot should be printed. A typical threshold value is 50% of the maximum theoretical image pixel intensity. For example, if there are 256 intensity levels (0 to 255) per pixel, a level of 128 may be chosen as the threshold value. In other error diffusion techniques, the threshold varies to avoid noticeable dot patterns being printed.
A well known error diffusion technique is described by R. Floyd and L. Steinberg in the paper Adaptive Algorithm for Spatial Grey Scale, SID Int'l. Sym. Digest of Tech. Papers, pp. 36-37 (1975), incorporated herein by reference. The Floyd and Steinberg error diffusion technique diffuses the error into a set of four surrounding pixels. Error diffusion with higher than four terms can also be used. U.S. Pat. No. 5,313,287 to David Barton, assigned to the present assignee and incorporated herein by reference, discloses another error diffusion technique.
When printing a color image, dots for three primary colors, cyan, magenta, and yellow, must be printed in various combinations to achieve the desired color tones to reproduce the original color image. Many known error diffusion methods operate on one color plane (e.g., cyan, magenta, or yellow) at a time. These types of error diffusion methods strive to generate a visually pleasing pattern of dots (i.e., dispersed dots) for each separate color, independent of the pattern of dots for the remaining colors. Due to random chance, these overlapping color dot patterns inevitably result in two or more dots of different colors overlapping or being adjacent to one another, as shown in FIG. 1, which is perceived by the human eye as a clumping of dots.
FIG. 1 illustrates an example of a prior art multi-colored dot pattern using magenta dots 4 and cyan dots 6. The overall tone is light blue. When the cyan and magenta planes overlap, non-pleasing dot patterns due to adjacent cyan and magenta dots (such as at location 7) can be formed due to random chance.